To elucidate the impact of pretransplant body mass index (BMI) on the clinical outcome, we performed a retrospective study with registry data including a total of 12 050 patients (age ⩾18 years) who received allogeneic hematopoietic SCT (HSCT) between 2000 and 2010. Patients were stratified as follows: BMI<18.5 kg/m2, Underweight, n=1791; 18.5⩽BMI<25, Normal, n=8444; 25⩽BMI<30, Overweight, n=1591; BMI⩾30, Obese, n=224. The median age was 45 years (range, 18–77). A multivariate analysis showed that the risk of relapse was significantly higher in the underweight group and lower in the overweight and obese groups compared with the normal group (hazard ratio (HR), 1.16, 0.86, and 0.74, respectively). The risk of GVHD was significantly higher in the overweight group compared with the normal group. The risk of non-relapse mortality (NRM) was significantly higher in the overweight and obese group compared with the normal group (HR 1.19 and HR 1.43, respectively). The probability of OS was lower in the underweight group compared with the normal group (HR 1.10, P=0.018). In conclusion, pretransplant BMI affected the risk of relapse and NRM after allogeneic HSCT. Underweight was a risk factor for poor OS because of an increased risk of relapse. Obesity was a risk factor for NRM.
Obesity has become an important health issue worldwide.1 On the other hand, malnutrition is an important problem in cancer patients.2 The impact of pretransplant obesity (high body mass index (BMI)) and malnutrition (low BMI) on the clinical outcome after allogeneic hematopoietic SCT (HSCT) is still controversial. Sorror et al.3 reported that obesity (BMI>35 kg/m2) as a factor in the hematopoietic cell transplant-specific comorbidity index was associated with an increased risk of non-relapse mortality (NRM). A large retrospective study from the Center for International Blood and Marrow Transplant Research (CIBMTR) showed that the probability of OS in patients with low BMI (BMI<18.5 kg/m2) was inferior to that in patients with a normal BMI in patients who received stem cells from either related or unrelated donors, mainly because of the increased risk of relapse.4 A limitation of this CIBMTR study was the limited number of patients with low BMI (32 of 2041 patients (1.6%) who received related HSCT and 33 of 1801 patients (1.8%) who received unrelated HSCT). We previously reported that there was a trend toward an increased risk of acute GVHD and NRM in patients with high BMI, and the risk of relapse was higher in patients with low BMI using registry data from the Japanese Marrow Donor Program.5 However, this study was limited by the small number of patients with high BMI (BMI⩾30 kg/m2) in this population (61 of 3935 patients (1.6%)). A larger database is needed to increase the statistical power, so that it would be sufficient to clarify the impact of both low BMI and high BMI simultaneously using a single database. In addition, a previous study did not reveal the characteristics of post transplant morbidity and mortality in patients with each risk factor.3 If we can clarify the details regarding the cause of failure in patients with low or high BMI, we may be able to improve the overall outcome after allogeneic HSCT. For this purpose, we assessed the impact of pretransplant BMI using a database from the Japan Society for Hematopoietic Cell Transplantation (JSHCT).6
Patients and methods
This study was approved by the Institutional Review Board of National Cancer Center, Tokyo, Japan. The patients in this analysis were aged 18 years or older, had received a first allogeneic HSCT between 2000 and 2010, and had data regarding pretransplant BMI. The patients' clinical data were obtained from the JSHCT database.6 Excluding patients without data regarding OS (n=30) as well as patients who received cord blood transplant (n=3621), 12 050 patients met the inclusion criteria and were included in the analysis. Patients were classified into four groups based on pretransplant BMI values according to consensus weight designations from the World Health Organization7 and the National Heart Lung and Blood Institute Expert Panel,8 as follows: underweight (BMI<18.5 kg/m2, n=1791), normal (18.5⩽BMI<25 kg/m2, n=8444), overweight (25⩽BMI<30 kg/m2, n=1591) and obese (BMI⩾30 kg/m2; n=224).
The study endpoints included GVHD, NRM, OS and relapse. Incidences of grade II–IV or III–IV acute and chronic or extensive chronic GVHD were based on classical criteria.9,10 OS was defined as time to death from any cause. NRM was defined as death from any cause in continuous CR or no progression. Relapse was defined as the time to onset of hematologic recurrence or disease progression.
A descriptive statistical analysis was performed to assess the patients’ characteristics. Medians and ranges are provided for continuous variables and percentages are shown for categorical variables. The patients’ characteristics were compared using the Chi-squared test for categorical variables. The probability of OS was calculated by the Kaplan–Meier method. A Cox proportional hazards regression model was used to analyze OS. The cumulative incidences of NRM and GVHD were evaluated using the Fine and Gray model for univariate and multivariate analyses. In the competing risk models for GVHD, relapse and death before these events were defined as competing risks. In the competing risk models for NRM, relapse was defined as a competing risk. For each cause-specific NRM, relapse and NRM with other causes were defined as competing risks. Factors that were associated with a two-sided P value of less than 0.10 in the univariate analysis were included in a multivariate analysis. We used a backward-stepwise selection algorithm and retained only the statistically significant variables in the final model. A two-sided P value of less than 0.05 was considered statistically significant. The variables evaluated in these analyses were as follows: sex mismatch (female to male vs other), patient’s age at the time of HSCT (age ⩾50 years vs age <50), disease risk (standard risk vs high risk), performance status (0–1 vs 2–4), stem cell source (related BM vs related PBSC vs unrelated BM), year of transplant (⩾2007 vs <2007) and HLA disparity as assessed by serological typing of HLA A, B and DRB1. In the analysis including the hematopoietic cell transplant-specific comorbidity index, we grouped patients into three groups (0 points vs 1–2 points vs ⩾3 points).3 Standard risk was defined as the first or second CR of acute leukemia, the first or second chronic phase of CML, myelodysplastic syndrome refractory anemia or refractory cytopenia with multilineage dysplasia, or nonmalignant disease. High risk was defined as other malignancies. Performance status was defined following ECOG criteria.11 We considered that the data are missing completely at random, and therefore, all analyses in this study were performed as available-case analyses. All statistical analyses were performed with EZR (Saitama Medical Center, Jichi Medical University, Tochigi, Japan), which is a graphical user interface for R (The R Foundation for Statistical Computing, version 3.0.2).12
The patient characteristics are shown in Table 1. The median age was 45 years (range, 18–77). The median follow-up of surviving patients was 1183 days after allogeneic HSCT. The underweight group included more patients with a poor performance status (14.7%) and female patients (59.0%) compared with the normal group. The obese group included younger patients and more patients with a myeloablative conditioning regimen (68.0%) and standard-risk disease (55.8%) compared with the normal group. Female patients had significantly higher BMI (mean, female 22.3 kg/m2, male 21.1 kg/m2, P<0.001). Gender-adjusted outcomes were less significant, and therefore gender was not included in the analysis.
The cumulative incidence of grade II–IV acute GVHD at 150 days was 35.7% in the underweight, 38.3% in normal, 42.2% in overweight and 37.6% in obese groups (P=0.002, Figure 1a). A multivariate analysis showed that overweight was associated with an increased risk of grade II–IV acute GVHD (hazard ratio (HR) 1.13, 95% confidence interval (CI) 1.03–1.24, P=0.011, Table 2). The cumulative incidence of grade III–IV acute GVHD was 12.7% in the underweight, 13.5% in normal, 16.8% in overweight and 15.9% in obese groups (P=0.004, Figure 1b). A multivariate analysis showed that being overweight was associated with an increased risk of grade III–IV acute GVHD (HR 1.27, 95%CI 1.10–1.48, P=0.002, Table 2). With regard to the target organ of acute GVHD, the incidence of skin GVHD was not significantly different among the four groups. On the other hand, the incidences of stage 2–4 liver and stage 2–4 gut acute GVHD were higher in patients who were overweight and obese. The cumulative incidence of stage 2–4 acute GVHD in the liver was 4.6% in the underweight, 5.5% in normal, 6.5% in overweight and 9.9% in obese groups (P=0.006, Figure 1c). A multivariate analysis showed that obesity was associated with an increased risk of stage 2–4 acute GVHD in the liver (HR 2.00, 95%CI 1.26–3.17, P=0.003, Supplementary Table 1). The cumulative incidence of stage 2–4 acute GVHD in the gut was 10.7% in the underweight, 11.2% in normal, 14.0% in overweight and 13.5% in obese groups (P=0.008, Figure 1d). A multivariate analysis showed that being overweight was associated with an increased risk of stage 2–4 acute GVHD in the gut (HR 1.30, 95%CI 1.10–1.53, P=0.002, Supplementary Table 1). The cumulative incidence of chronic GVHD at 2 years was 32.5% in the underweight, 35.8% in normal, 36.6% in overweight and 40.1% in obese groups (P=0.042, Figure 1e). In a multivariate analysis, BMI was not a significant risk factor for chronic GVHD. The cumulative incidence of extensive chronic GVHD was 19.9% in the underweight, 23.7% in normal, 24.9% in overweight and 28.4% in obese groups (P=0.001, Figure 1f). A multivariate analysis showed that obesity was associated with an increased risk of extensive chronic GVHD (HR 1.32, 95%CI 1.01–1.74, P=0.043, Supplementary Table 1).
The cumulative incidence of NRM at 2 years was 19.5% in the underweight, 21.9% in normal, 25.1% in overweight and 23.0% in obese groups (P=0.002, Figure 2a). A multivariate analysis showed that overweight and obesity were each associated with an increased risk of NRM (HR 1.19, 95%CI 1.06–1.33, P=0.004; HR 1.43, 95%CI 1.08–1.88, P=0.012, Table 3). Only 30 of the 12 050 patients had a BMI>35 kg/m2 (0.25%). In these patients, the cumulative incidence of NRM at 2 years was 25.6%. The cumulative incidence of infection-related NRM at 2 years was 5.7% in the underweight, 6.3% in normal, 7.7% in overweight and 5.2% in obese groups (P=0.021, Figure 2b). A multivariate analysis showed that overweight was associated with an increased risk of infection-related NRM (HR 1.34, 95% CI 1.09–1.64, P=0.006). The cumulative incidence of GVHD-related NRM at 2 years was 2.3% in the underweight, 3.1% in normal, 4.5% in overweight and 5.1% in obese groups (P=0.002, Figure 2c). A multivariate analysis showed that obesity was associated with an increased risk of GVHD-related NRM (HR 2.15, 95% CI 1.20–3.86, P=0.010). In patients who developed grade II–IV acute GVHD, the cumulative incidence of 2-year NRM after acute GVHD was 23.8% in the underweight, 28.8% in normal, 32.6% in overweight and 34.1% in obese groups (P=0.001). A multivariate analysis showed that overweight and obesity were each associated with an increased risk of NRM in patients who developed grade II–IV acute GVHD (HR 1.18, 95% CI 1.01–1.39, P=0.040; HR 1.62, 95%CI 1.09–2.42, P=0.018). In patients who developed grade III–IV acute GVHD, the cumulative incidence of 2-year NRM after acute GVHD was 39.7% in the underweight, 49.4% in normal, 53.8% in overweight and 59.0% in obese groups (P=0.003). A multivariate analysis showed that underweight and obesity were associated with a decreased and increased risk of NRM, respectively, in patients who developed grade III–IV acute GVHD (HR 0.72, 95% CI 0.56–0.92, P=0.009; HR 1.65, 95% CI 1.01–2.71, P=0.048).
We also assessed the impact of BMI on NRM in a multivariate analysis that included hematopoietic cell transplant-specific comorbidity index scores. In a multivariate analysis that included hematopoietic cell transplant-specific comorbidity index (0 points vs 1–2 points vs ⩾3 points), overweight and obesity were each still associated with an increased risk of NRM (HR 1.26, 95% CI 1.05–1.50, P=0.012; HR 1.54, 95% CI 1.05–2.26, P=0.029).
The cumulative incidence of relapse/progression was 35.6% in the underweight, 30.5% in normal, 23.9% in overweight and 22.6% in obese groups (P<0.0001, Figure 2d). A multivariate analysis showed that underweight was associated with a higher risk of relapse (HR 1.16, 95% CI 1.06–1.28, P=0.002), and overweight and obesity were each associated with a lower risk of relapse (HR 0.86, 95% CI 0.77–0.96, P=0.008; HR 0.74, 95% CI 0.56–0.99, P=0.045, Table 4). In patients with BMI⩾35 kg/m2, the cumulative incidence of relapse at 2 years was 18.4%. We conducted a subgroup analysis according to the underlying hematological malignancies. In patients with AML, the cumulative incidence of relapse/progression was 43.5% in the underweight, 35.5% in normal, 28.3% in overweight and 28.6% in obese groups (P<0.0001). In patients with ALL, the cumulative incidence of relapse/progression was 31.9% in the underweight, 28.9% in normal, 21.8% in overweight and 22.1% in obese groups (P=0.091).
The probability of OS at 2 years after allogeneic HSCT was 49.4% in the underweight, 53.0% in normal, 54.9% in overweight and 63.5% in obese groups (P=0.002, Figure 2e). A multivariate analysis showed that underweight was associated with a worse OS than that in the normal group (HR 1.10, 95% CI 1.02–1.19, P=0.018, Table 4).
We conducted a subgroup analysis according to the conditioning regimen. In patients who received a conventional CY plus TBI-based myeloablative conditioning regimen, the cumulative incidence of relapse/progression was 33.6% in the underweight, 28.8% in normal, 23.1% in overweight and 23.6% in obese groups (P<0.0001), and the cumulative incidence of NRM was 17.1% in the underweight, 21.0%in normal, 25.3% in overweight and 23.9% in obese groups (P=0.003). In patients who received a BU plus CY-based myeloablative conditioning regimen, the cumulative incidence of relapse/progression was 38.9% in the underweight, 27.2% in normal, 20.7% in overweight and 13.5% in obese groups (P=0.001), and the cumulative incidence of NRM was 18.9% in the underweight, 22.2% in normal, 25.8% in overweight and 17.1% in obese groups (P=0.47). In patients who received a reduced-intensity conditioning regimen, the cumulative incidence of relapse/progression was 35.0% in the underweight, 33.2% in normal, 25.5% in overweight and 22.8% in obese groups (P=0.018), and the cumulative incidence of NRM was 22.0% in the underweight, 21.7% in normal, 25.9% in overweight and 22.4% in obese groups (P=0.13).
Here, we demonstrated that pretransplant BMI significantly influenced the post-transplant clinical outcome. To our knowledge, this is the largest study on the impact of pretransplant BMI after allogeneic HSCT. Our study showed that patients with a low BMI had the worst OS because of an increased risk of relapse, whereas patients with a high BMI had the highest NRM because of an increased risk of GVHD-related NRM.
Regarding the impact of obesity, Sorror et al.3 reported that obesity (BMI>35 kg/m2) was associated with an increased risk of NRM. However, in Japan and many other countries, the prevalence of patients with BMI>35 kg/m2 is rather low, as shown in this study and previous reports.1,5 A previous study showed that the mean BMIs in the US and Japan were 28 kg/m2 and 22 kg/m2, respectively, which shows that there is a huge difference in BMI between the two countries.1 In the current study, only 30 of the 12 050 total patients had BMI>35 kg/m2 (0.25%). Although the risk of NRM in patients with BMI>35 kg/m2 tended to be higher than that in patients with normal BMI (2-year NRM 25.6% vs 21.9%), this difference was not statistically significant, possibly because of the limited number of patients. Theoretically, Japanese patients compared to Caucasian patients should have less GVHD because of less HLA gene variability and less obesity because of diet. Therefore, the findings of this study could be even more pronounced in Caucasian patients, which should be assessed using data of Caucasian patients.
In the current study, obese patients (BMI⩾30 kg/m2) had a higher risk of NRM, and particularly GVHD-related NRM, compared with those with normal BMI. In addition, obese patients had a worse outcome than those with normal BMI when patients developed grade II–IV or grade III–IV acute GVHD. One possible reason why obese patients had a higher risk of GVHD-related death is the higher incidences of hepatic and gut acute GVHD in comparison with patients with normal BMI, which have been reported to be associated with a poor response to GVHD therapy and an increased risk of NRM.13, 14, 15, 16 One hypothesis is that the greater tissue damage caused by the higher dose of chemotherapy in obese patients may contribute to the induction of cytokine storms, which leads to severe acute GVHD.17 Another hypothesis is that the different immune status in obesity affects the functional status of immune cells after allogeneic HSCT. It has been reported that, in obese patients, the number of adipose tissue-resident immune cells, such as macrophages, CD8+ T cells and IFN-γ Th1+ cells, is increased, and the number of regulatory T cells is decreased.18, 19, 20 Such an obesity-induced shift in adipose tissue-resident immune cells might increase the alloimmune reaction after allogeneic HSCT as reported in the field of organ transplantation, as reviewed previously.21 Intriguingly, previous studies have reported that Caucasian patients had an increased risk of acute GVHD compared to Asian patients.22,23 The huge difference in BMI among races might at least partially influence the incidence of acute GVHD.
The obese patients in this study had a substantially increased risk of stage 2–4 acute GVHD in the liver (HR 2.00, 95% CI 1.26–3.17). Considering the mortality associated with hepatic acute GVHD, we should intervene to reduce the risk of hepatic acute GVHD in obese patients.13, 14, 15, 16 It is well-known that a prominent obesity-induced immune shift in the liver, so-called non-alcoholic steatohepatitis, causes inflammation in the liver, which might contribute to the subsequent increased risk of hepatic acute GVHD.18,24 Practically, careful monitoring and early institution of high-dose immunosuppression are suggested. As a possible intervention, weight loss by diet and exercise could be a safe option, and has been shown to dose-dependently improve histological disease activity in non-alcoholic steatohepatitis associated with obesity.25,26
In terms of the impact of being underweight, several previous studies have also reported that being underweight was associated with a poor outcome after allogeneic HSCT.4,27,28 Navarro et al.4 has reported that OS in AML patients with BMI at transplant <18 was inferior to that in patients with a normal BMI in patients who received stem cells from related donors, but not in the unrelated donor group. In terms of relapse, the relative risk of relapse was reduced for the overweight (relative risk 0.82, 95%CI 0.68–0.99, P=0.044) and obese (relative risk 0.76, 95% CI 0.0.60–0.96, P=0.022) groups. However, in terms of disease-free survival (Figure 2b in Navarro et al.4), there was a clear trend that the outcome in AML patients with BMI at transplant <18 was inferior to that in patients with a normal BMI in patients who received stem cells from unrelated donors. The lack of statistical significance in unrelated HSCT might be because of a lack of power in the study (33 in 1801 patients). Underweight patients may have had more advanced disease compared with those with higher BMI, even though the proportion of patients with advanced disease was the same in the underweight and normal groups in this study. Shorter interval between diagnosis and transplant in the underweight group might suggest the aggressive nature of underlying disease. In a multivariate analysis, being underweight was associated with an increased risk of relapse independent of performance status and disease risk. When we performed a subgroup analysis that included only patients with high-risk disease, being underweight was still independently associated with a poor OS because of a significantly increased risk of relapse compared with the normal group (HR 1.11, 95% CI 1.01–1.22, P=0.027). Furthermore, even when we grouped patients according to the conditioning regimen, the cumulative incidence of relapse was significantly higher in the underweight group compared with the other groups, irrespective of the type of the conditioning regimen. One possible explanation for why underweight patients had an increased risk of relapse is the insufficient dosage of chemotherapy compared with those in the other groups. In underweight patients, actual body weight is usually used to calculate the dose of chemotherapy. Therefore, the dose of chemotherapy in underweight patients should be lower than those in patients with normal or heavier body weight, considering the dose per ideal body weight. However, it is uncertain whether the adjusted dose of chemotherapy using an ideal body weight in patients with low BMI could lead to a better outcome without an increased risk of morbidities. In addition, several previous reports showed that the status of nutrition had an impact on the metabolism of the chemotherapeutic drugs.29,30 For instance, nutritional status was reported to affect the level of cytochrome P450 enzymes which are responsible for the metabolism of the chemotherapeutic drugs. It was reported that there was a correlation between total body weight and plasma half-life of CY, which means that the concentration of CY is higher in obese patients compared with the normal weight patients.31 Such changes in the metabolism of chemotherapeutic drugs might affect the risk of relapse and NRM in the setting of allogeneic HSCT.
An intervention that may improve the outcome is the amelioration of body weight loss before allogeneic HSCT. In general nutrition screening, BMI<18.5 kg/m2 is defined as an impaired nutritional status according to the European Society of Parenteral and Enteral Nutrition guidelines for 2002.32 It may be possible to at least partially prevent pretransplant weight loss with some intervention including lifestyle modification, such as intensive nutritional support and exercise during induction and consolidation chemotherapy.33,34 Exercise is important for maintaining skeletal muscle mass, and sufficient nutritional support is essential for preventing catabolism, since previous reports have demonstrated a high prevalence of sarcopenia before allogeneic HSCT.33, 34, 35
This study has some limitations. Because of the nature of the registry database, we were not able to assess the policies regarding adjustment of the conditioning regimen dose for patients with obesity, which will likely vary among the transplant centers. Another important limitation is that we included almost exclusively Japanese patients. Therefore, it is uncertain whether similar findings would be seen in other countries/regions. Our findings should be reassessed using other databases. Furthermore, because of the nature of the registry database, we were not able to assess the change of body weight and anthropometric measures before allogeneic HSCT. Although no standardized nutritional screening tool has been designed specifically for use in patients who undergo allogeneic HSCT, weight loss and anthropometric measures is in general regarded as an integral part of nutritional screening in most nutritional screening tool.32,36,37 A recent study reported that pretransplant low arm muscle area was a stronger predictor than BMI of poor outcomes after HCT in children with hematologic malignancies.38 The impact of pretransplant BMI, anthropometric measures and change of body weight should be assessed in the future studies.
In conclusion, we demonstrated that pretransplant BMI significantly affected the major post-transplant outcome. A prospective study to assess the impact of intervention including nutritional support and exercise is warranted.
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We thank the medical, nursing, data-processing, laboratory and clinical staffs at the participating centers for their important contributions to this study and their dedicated care of the patients. This study was supported in part by grants from the Ministry of Health, Labor and Welfare, Japan.
The authors declare no conflict of interest.
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Fuji, S., Takano, K., Mori, T. et al. Impact of pretransplant body mass index on the clinical outcome after allogeneic hematopoietic SCT. Bone Marrow Transplant 49, 1505–1512 (2014) doi:10.1038/bmt.2014.178
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